Segmentation morphologique interactive pour la fouille de séquences vidéo. (Interactive morphological segmentation for video mining)

Nous observons actuellement une augmentation importante du volume de donnees video disponibles. L'utilisation efficace de cette masse de donnees necessite d'en extraire de l'information. Dans cette these, nous proposons d'utiliser les methodes de fouille de donnees et de les appliquer sur les objets-video d'interet afin de combler le fosse semantique en impliquant l'utilisateur dans le processus. Extraire ces objets a partir des pixels necessite de manipuler un grand volume de donnees, induisant un traitement couteux (en temps et en memoire) peu compatible avec une implication interactive de l'utilisateur. Ainsi, nous proposons d'appliquer le processus interactif de segmentation sur une reduction des donnees, les zones quasi-plates. N'etant definies que pour les images fixes, nous proposons une extension des zones quasi-plates aux sequences video ainsi qu'une nouvelle methode de filtrage. La segmentation est effectuee interactivement par l'utilisateur qui dessine des marqueurs sur les objets d'interet afin de guider la fusion des zones quasi-plates composant ces objets. Elle est effectuee sur un graphe d'adjacence de regions representant les zones quasi-plates spatiotemporelles ainsi que leurs relations d'adjacence. L'utilisation de cette structure assure un faible temps de calcul. Les objets-video obtenus sont ensuite utilises dans un processus de fouille interactif guide par des descripteurs extraits automatiquement de la video et des informations donnees par l'utilisateur. La forte interactivite avec l'utilisateur, a la fois lors de l'etape de segmentation puis lors de l'etape de fouille favorise la synergie entre donnees numeriques et interpretation humaine.

[1]  Y. J. Zhang,et al.  A survey on evaluation methods for image segmentation , 1996, Pattern Recognit..

[2]  Luís Corte-Real,et al.  Video object matching across multiple independent views using local descriptors and adaptive learning , 2009, Pattern Recognit. Lett..

[3]  Tsuhan Chen,et al.  Video retrieval based on object discovery , 2009, Comput. Vis. Image Underst..

[4]  Pierre Gançarski,et al.  Video Object Mining: Issues and Perspectives , 2010, 2010 IEEE Fourth International Conference on Semantic Computing.

[5]  Chabane Djeraba,et al.  Kpyr, une structure efficace d'indexation de documents vidéo , 2005, INFORSID.

[6]  Xiaojin Zhu,et al.  --1 CONTENTS , 2006 .

[7]  John MacCormick,et al.  Fast superpixels for video analysis , 2009, 2009 Workshop on Motion and Video Computing (WMVC).

[8]  Jesús Angulo,et al.  Color segmentation by ordered mergings , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[9]  Shih-Fu Chang,et al.  Clustering methods for video browsing and annotation , 1996, Electronic Imaging.

[10]  Pavel Berkhin,et al.  A Survey of Clustering Data Mining Techniques , 2006, Grouping Multidimensional Data.

[11]  Ellen M. Voorhees,et al.  Implementing agglomerative hierarchic clustering algorithms for use in document retrieval , 1986, Inf. Process. Manag..

[12]  Sébastien Lefèvre,et al.  Segmentation vidéo interactive par zones quasi-plates , 2011 .

[13]  Pierre Soille,et al.  Iterative area filtering of multichannel images , 2007, Image Vis. Comput..

[14]  Sébastien Chabrier Contribution à l'évaluation de performances en segmentation d'images , 2005 .

[15]  A. Enis Çetin,et al.  Moving object detection in wavelet compressed video , 2005, Signal Process. Image Commun..

[16]  Aggelos K. Katsaggelos,et al.  Anomalous video event detection using spatiotemporal context , 2011 .

[17]  Jean Ponce,et al.  Discriminative clustering for image co-segmentation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Hayit Greenspan,et al.  Probabilistic space-time video modeling via piecewise GMM , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Jun Zhang,et al.  Video mining: concepts, approaches and applications , 2006, 2006 12th International Multi-Media Modelling Conference.

[20]  Ajay Divakaran,et al.  MPEG-7 visual motion descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[21]  Stefanie Zollmann,et al.  Incremental Superpixels for Real-Time Video Analysis , 2011 .

[22]  Miroslaw Bober,et al.  MPEG-7 visual shape descriptors , 2001, IEEE Trans. Circuits Syst. Video Technol..

[23]  Yu Jin Zhang,et al.  A review of recent evaluation methods for image segmentation , 2001, Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467).

[24]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[25]  Anil K. Jain,et al.  Unsupervised Learning of Finite Mixture Models , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Alexandre Carleer,et al.  Assessment of Very High Spatial Resolution Satellite Image Segmentations , 2005 .

[27]  Jérémy Huart,et al.  Extraction et analyse d'objets-clés pour la structuration d'images et de vidéos. (Extraction and Analysis of Key-Objects for Image and Video Structuring) , 2007 .

[28]  Alvy Ray Smith,et al.  Color gamut transform pairs , 1978, SIGGRAPH.

[29]  Ulisses Braga-Neto,et al.  A Theoretical Tour of Connectivity in Image Processing and Analysis , 2003, Journal of Mathematical Imaging and Vision.

[30]  Chu-Song Chen,et al.  MOMI-Cosegmentation: Simultaneous Segmentation of Multiple Objects among Multiple Images , 2010, ACCV.

[31]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[32]  Sébastien Lefèvre,et al.  On the morphological processing of hue , 2009, Image Vis. Comput..

[33]  S. Lefèvre,et al.  Fouille vidéo orientée objet, une approche générique , 2011 .

[34]  Marie-Pierre Jolly,et al.  Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[35]  Mei Han,et al.  Efficient hierarchical graph-based video segmentation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[36]  Zhi Liu,et al.  Semi-automatic video object segmentation using seeded region merging and bidirectional projection , 2005, Pattern Recognit. Lett..

[37]  Mickael Guironnet Méthodes de résumé de vidéo à partir d'informations bas niveau, du mouvement de caméra ou de l'attention visuelle , 2006 .

[38]  Maneesh Kumar Singh,et al.  State-of-the-art on spatio-temporal information-based video retrieval , 2009, Pattern Recognit..

[39]  Sudipto Guha,et al.  CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.

[40]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[41]  A. Baddeley An Error Metric for Binary Images , 1992 .

[42]  Makoto Nagao,et al.  Region extraction and shape analysis in aerial photographs , 1979 .

[43]  Jesús Angulo Morphologie mathématique et indexation d'images couleur : application à la microscopie en biomédecine. (Mathematical morphology and image colour indexing : application in bio-medical microscopy) , 2003 .

[44]  Allan Hanbury,et al.  A 3D-Polar Coordinate Colour Representation Well Adapted to Image Analysis , 2003, SCIA.

[45]  Robin Sibson,et al.  SLINK: An Optimally Efficient Algorithm for the Single-Link Cluster Method , 1973, Comput. J..

[46]  Thomas Sikora,et al.  The MPEG-7 visual standard for content description-an overview , 2001, IEEE Trans. Circuits Syst. Video Technol..

[47]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[48]  Sébastien Lefèvre,et al.  Approches multivaluées et supervisées en morphologie mathématique et applications en analyse d'image. (Multivalued and Supervised Approaches within Mathematical Morphology, and Applications in Image Analysis) , 2009 .

[49]  Ming-Chieh Lee,et al.  Semiautomatic segmentation and tracking of semantic video objects , 1998, IEEE Trans. Circuits Syst. Video Technol..

[50]  Song Wang,et al.  New benchmark for image segmentation evaluation , 2007, J. Electronic Imaging.

[51]  Ferran Marqués,et al.  Tracking of generic objects for video object generation , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[52]  Florian Schroff,et al.  Clustering Videos by Location , 2009, BMVC.

[53]  Roberto Cipolla,et al.  Semantic object classes in video: A high-definition ground truth database , 2009, Pattern Recognit. Lett..

[54]  Guizhong Liu,et al.  A semantic framework for video genre classification and event analysis , 2010, Signal Process. Image Commun..

[55]  Wei Ren,et al.  A Video Summarization Approach Based on Machine Learning , 2008, 2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[56]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[57]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[58]  Hsuan-Ting Chang,et al.  Efficient Moving Object Extraction in Compressed Low-Bit-Rate Video , 2006, 2006 International Conference on Intelligent Information Hiding and Multimedia.

[59]  Scott Cohen,et al.  LIVEcut: Learning-based interactive video segmentation by evaluation of multiple propagated cues , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[60]  Pierre Gançarski,et al.  Spatio-temporal Quasi-Flat Zones for Morphological Video Segmentation , 2011, ISMM.

[62]  F. Meyer,et al.  ON THE IMPLEMENTATION OF NON-SEPARABLE VECTOR LEVELINGS , 2002 .

[63]  Sébastien Lefèvre,et al.  A comparative study on multivariate mathematical morphology , 2007, Pattern Recognit..

[64]  Cedric Nishan Canagarajah,et al.  A Novel Video Mining System , 2007, 2007 IEEE International Conference on Image Processing.

[65]  Pierre Soille,et al.  Constrained connectivity for the processing of very-high-resolution satellite images , 2010 .

[66]  Christophe Charle,et al.  Liste des tableaux , 1988 .

[67]  Roberto de Alencar Lotufo,et al.  Watershed from propagated markers: An interactive method to morphological object segmentation in image sequences , 2010, Image Vis. Comput..

[68]  Vincent Claveau,et al.  Topic Segmentation: Application of Mathematical Morphology to Textual Data , 2011, ISMM.

[69]  Germain Forestier,et al.  Supervised image segmentation using watershed transform, fuzzy classification and evolutionary computation , 2010, Pattern Recognit. Lett..

[70]  Pierre Soille,et al.  Constrained Connectivity and Transition Regions , 2009, ISMM.

[71]  J. MacQueen Some methods for classification and analysis of multivariate observations , 1967 .

[72]  Daniel P. Fasulo,et al.  An Analysis of Recent Work on Clustering Algorithms , 1999 .

[73]  Noel E. O'Connor,et al.  A comparative evaluation of interactive segmentation algorithms , 2010, Pattern Recognit..

[74]  Cedric Nishan Canagarajah,et al.  Object based video retrieval with local region tracking , 2007, Signal Process. Image Commun..

[75]  Jenny Benois-Pineau,et al.  Retrieval of objects in video by similarity based on graph matching , 2007, Pattern Recognit. Lett..

[76]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[77]  Maria Fransisca Zanoguera Tous Segmentation interactive d'images fixes et de séquences vidéo basée sur des hiérarchies de partitions , 2001 .

[78]  Jung-Hwan Oh,et al.  Clustering of Video Objects by Graph Matching , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[79]  Pierre Soille,et al.  Constrained connectivity for hierarchical image partitioning and simplification , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[80]  Cordelia Schmid,et al.  A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.

[81]  Paulo Lobato Correia,et al.  A video object generation tool allowing friendly user interaction , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[82]  Philippe Salembier,et al.  Flat zones filtering, connected operators, and filters by reconstruction , 1995, IEEE Trans. Image Process..

[83]  Andrew Zisserman,et al.  Efficient Visual Search for Objects in Videos , 2008, Proceedings of the IEEE.

[84]  Diane J. Cook,et al.  Automatic Video Classification: A Survey of the Literature , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[85]  Xin He,et al.  Parallel Algorithms for Gray-Scale Digitized Picture Component Labeling on a Mesh-Connected Computer , 1994, J. Parallel Distributed Comput..

[86]  José Crespo,et al.  The flat zone approach: A general low-level region merging segmentation method , 1997, Signal Process..

[87]  M. Pellegrini,et al.  On Using Clustering Algorithms to Produce Video Abstracts for the Web Scenario , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.

[88]  Sethuraman Panchanathan,et al.  Review of Image and Video Indexing Techniques , 1997, J. Vis. Commun. Image Represent..

[89]  G. Matheron Éléments pour une théorie des milieux poreux , 1967 .

[90]  Jean Paul Frédéric Serra Connectivity on Complete Lattices , 2004, Journal of Mathematical Imaging and Vision.

[91]  Philippe Salembier,et al.  Connected operators and pyramids , 1993, Optics & Photonics.

[92]  Dmitry Chetverikov,et al.  A Brief Survey of Dynamic Texture Description and Recognition , 2005, CORES.

[93]  Fernando Pereira,et al.  Objective evaluation of relative segmentation quality , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[94]  R. Zéboudj,et al.  Filtrage, seuillage automatique, contraste et contours : du pré-traitement à l'analyse d'image , 1988 .

[95]  Mounia Lalmas,et al.  A survey on the use of relevance feedback for information access systems , 2003, The Knowledge Engineering Review.

[96]  Vladimir Kolmogorov,et al.  Cosegmentation Revisited: Models and Optimization , 2010, ECCV.

[97]  Paulo Villegas,et al.  Perceptually-weighted evaluation criteria for segmentation masks in video sequences , 2004, IEEE Transactions on Image Processing.

[98]  Harry W. Agius,et al.  Video summarisation: A conceptual framework and survey of the state of the art , 2008, J. Vis. Commun. Image Represent..

[99]  Azriel Rosenfeld,et al.  Scene analysis using region-based constraint filtering , 1984, Pattern Recognit..

[100]  G. Matheron Random Sets and Integral Geometry , 1976 .

[101]  Paul Over,et al.  Video shot boundary detection: Seven years of TRECVid activity , 2010, Comput. Vis. Image Underst..

[102]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[103]  Christophe Collet,et al.  Toward a New Axiomatic for Hyper-Connections , 2011, ISMM.

[104]  Michael H. F. Wilkinson,et al.  Hyperconnected Attribute Filters Based on k-Flat Zones , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[105]  Francesca Manerbaa,et al.  REAL-TIME ROUGH EXTRACTION OF FOREGROUND OBJECTS IN MPEG 1 , 2 COMPRESSED VIDEO , 2005 .

[106]  Guojun Lu,et al.  Shape-based image retrieval using generic Fourier descriptor , 2002, Signal Process. Image Commun..

[107]  Paul Over,et al.  Evaluation campaigns and TRECVid , 2006, MIR '06.

[108]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[109]  Arnaldo de Albuquerque Araújo,et al.  VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method , 2011, Pattern Recognit. Lett..

[110]  Nevenka Dimitrova,et al.  Video Clustering Using SuperHistograms in Large Archives , 2000, VISUAL.

[111]  Mubarak Shah,et al.  Content based video matching using spatiotemporal volumes , 2008, Comput. Vis. Image Underst..

[112]  Pierre Gançarski,et al.  Interactive video segmentation based on quasi-flat zones , 2011, 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA).

[113]  Shih-Fu Chang,et al.  Image Retrieval: Current Techniques, Promising Directions, and Open Issues , 1999, J. Vis. Commun. Image Represent..

[114]  RosenfeldAzriel,et al.  Sequential Operations in Digital Picture Processing , 1966 .

[115]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[116]  Vladimir Kolmogorov,et al.  An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision , 2001, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[117]  Jiebo Luo,et al.  Seed Image Selection in interactive cosegmentation , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[118]  Jesús Angulo López Morphologie mathématique et indexation d'image couleur : application à la microscopie en biomédecine , 2003 .

[119]  Jean Paul Frédéric Serra,et al.  A Lattice Approach to Image Segmentation , 2005, Journal of Mathematical Imaging and Vision.

[120]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[121]  R. Venkatesh Babu,et al.  Video object segmentation: a compressed domain approach , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[122]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[123]  Nevenka Dimitrova,et al.  Color superhistograms for video representation , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[124]  Tian Zhang,et al.  BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.

[125]  Pierre Soille,et al.  Pattern Spectra from Partition Pyramids and Hierarchies , 2011, ISMM.

[126]  Olivier Buisson,et al.  Scalable mining of large video databases using copy detection , 2008, ACM Multimedia.

[127]  Xuelong Li,et al.  Shot-based video retrieval with optical flow tensor and HMMs , 2009, Pattern Recognit. Lett..

[128]  Gabriela Csurka,et al.  Visual categorization with bags of keypoints , 2002, eccv 2004.

[129]  Michael H. F. Wilkinson An Axiomatic Approach to Hyperconnectivity , 2009, ISMM.

[130]  Antonio Torralba,et al.  LabelMe video: Building a video database with human annotations , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[131]  Ramesh C. Jain,et al.  A survey on the use of pattern recognition methods for abstraction, indexing and retrieval of images and video , 2002, Pattern Recognit..

[132]  Petros Maragos,et al.  Morphological Scale-Space Representation with Levelings , 1999, Scale-Space.

[133]  Serge Beucher,et al.  Marker-controlled segmentation: an application to electrical borehole imaging , 1992, J. Electronic Imaging.

[134]  Dan Klein,et al.  Interpreting and Extending Classical Agglomerative Clustering Algorithms using a Model-Based approach , 2002, ICML.

[135]  Hui Zhang,et al.  Image segmentation evaluation: A survey of unsupervised methods , 2008, Comput. Vis. Image Underst..

[136]  Peter J. Rousseeuw,et al.  Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .

[137]  Martin D. Levine,et al.  Dynamic Measurement of Computer Generated Image Segmentations , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[138]  Rama Chellappa,et al.  Unsupervised view and rate invariant clustering of video sequences q , 2009 .

[139]  B. S. Manjunath,et al.  Video Annotation Through Search and Graph Reinforcement Mining , 2010, IEEE Transactions on Multimedia.

[140]  Pierre Soille On Genuine Connectivity Relations Based on Logical Predicates , 2007, 14th International Conference on Image Analysis and Processing (ICIAP 2007).

[141]  George Economou,et al.  Combining graph connectivity & dominant set clustering for video summarization , 2009, Multimedia Tools and Applications.

[142]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[143]  LefèvreSébastien,et al.  A review of real-time segmentation of uncompressed video sequences for content-based search and retrieval , 2003 .

[144]  Pierre Soille Preventing Chaining through Transitions While Favouring It within Homogeneous Regions , 2011, ISMM.

[145]  Andrew McCallum,et al.  Semi-Supervised Clustering with User Feedback , 2003 .

[146]  Bin Luo,et al.  Video Abstraction Based on Relational Graphs , 2007, Fourth International Conference on Image and Graphics (ICIG 2007).